On Apr 6, 2010, at 9:08 AM, David Cournapeau wrote:
> Hi Travis,
>> On Tue, Apr 6, 2010 at 7:43 AM, Travis Oliphant <oliphant@enthought.com> > wrote:
>>>>>> I should have some time over the next couple of weeks, and I am very
>> interested in refactoring the NumPy code to separate out the Python
>> interface layer from the "library" layer as much as possible. I had
>> some discussions with people at PyCon about making it easier for
>> Jython, IronPython, and perhaps even other high-level languages to
>> utilize NumPy.
>>>> Is there a willingness to consider as part of this reorganization
>> creating a clear boundary between the NumPy library code and the
>> Python-specific interface to it? What other re-organization
>> thoughts
>> are you having David?
>> This is mainly it, reorganizing the code for clearer boundaries
> between boilerplate (python C API) and actual compuational code.
> Besides helping other python implementations, I think this would
> benefit NumPy itself in the long run (code maintainability), as well
> as scipy (and other C extensions). I think the npymath effort is a
> good example: albeit simple in nature (the API and boundaries are
> obvious), it has already helped a lot to solve numerous platform
> specific issues in numpy and scipy, and I think the overall code
> quality is better.
>> My own goals were:
> - exposing core computational parts through an exported C API, so
> that other C extensions may use it (for example, exposing basic
> blas/lapack operations)
> - dynamic loading of the code (for example depending on the CPU
> capabilities - I have a git branch somewhere where I started exposing
> a simple C API to query cpu capabilities like cache size or SSE
> dynamically to that intent)
> - more amenable codebase: I think multiarray in particular is too
> big. I don't know the code well enough to know what can be split and
> how, but I would have hoped that the scalartypes, the type descriptor
> could be put out of multiarray proper. Also, exposing an API for
> things like fancy indexing would be very useful, but I don't know if
> it even makes sense - I think a pure python implementation of fancy
> indexing as a reference would be very useful for array-like classes (I
> am thinking about scipy.sparse, for example).
>> Unfortunately, I won't be able to help much in the near future (except
> maybe for the fancy indexing as this could be useful for my job),
>
I understand. It just happens that there is some significant time
for me to look at this over the next few weeks and I would really like
to make progress on re-factoring. I think it's O.K. if you don't
have time right now to help as long as you have time to offer
criticism and suggestions.
We could even do that over Skype with whomever else wanted to join us
(we could do a GotoMeeting discussion as well) if you think it would
be faster to just talk in a group setting instead of email. Of
course, a summary of any off-line discussion should be sent to the list.
Thanks for the input,
-Travis
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